class_docstr: Searches for structured entities, e.g. dates, using a duckling server.
docstr: Augments the message with potentially extracted entities.
docstr_tok: ["Augments","the","message","with","potentially","extracted","entities","."]
code: def process(self, messages: List[Message]) -> List[Message]:
      """Augments the message with potentially extracted entities."""
      if self._url() is None:
          rasa.shared.utils.io.raise_warning(
              "Duckling HTTP component in pipeline, but no "
              "`url` configuration in the config "
              "file nor is `RASA_DUCKLING_HTTP_URL` "
              "set as an environment variable. No entities will be extracted!",
              docs=DOCS_URL_COMPONENTS + "#DucklingEntityExtractor",
          )
          return messages
  
      for message in messages:
          reference_time = self._reference_time_from_message(message)
          matches = self._duckling_parse(
              message.get(TEXT), reference_time
          )
          all_extracted = convert_duckling_format_to_rasa(matches)
          dimensions = self.component_config["dimensions"]
          extracted = self.filter_irrelevant_entities(
              all_extracted, dimensions
          )
          extracted = self.add_extractor_name(extracted)
          message.set(
              ENTITIES,
              message.get(ENTITIES, []) + extracted,
              add_to_output=True,
          )
  
      return messages
  
imports: from __future__ import annotations
  import time
  import json
  import logging
  import os
  import requests
  from typing import Any, List, Optional, Text, Dict
  import rasa.utils.endpoints
  from rasa.engine.graph import GraphComponent, ExecutionContext
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.shared.constants import DOCS_URL_COMPONENTS
  from rasa.shared.nlu.constants import ENTITIES, TEXT
  from rasa.nlu.extractors.extractor import EntityExtractorMixin
  from rasa.shared.nlu.training_data.message import Message
  import rasa.shared.utils.io
label_desc: Use image node_id 8 for calling the DucklingEntityExtractor obj's underlying member method code with example usage: obj.process(messages) and returns: messages, messages